Automated systems may use video analytic systems and processes to distinguish objects of interest that are visible within the video data from other visual elements, and to thereby enable detection and observation of said objects in processed video data input. Such information processing systems may receive images or image frame data captured by video cameras or other image capturing devices, wherein the images or frames are processed or analyzed by an object detection system in the information processing system to identify objects within the images.
The image data for the identified objects may also be analyzed for attributes of the objects, including defects or irregularities associated with the objects. For example, object detection systems may identify objects of interest such as a railroad track and its components (e.g., ties, tie plates, anchors, joint bars, etc.) and use a variety of automated processes to attempt to determine and report if defects or irregularities exist with respect to said objects such as, but not limited to, missing ties, missing spikes, damaged joint bars, damaged rails, etc. Automatic vision-based rail inspection systems may provide more efficiency and reliable performance than human inspectors when provided high quality images as input. However, such systems may perform poorly, missing or falsely reporting defects, due to image problems that may prevent object identification, such as occlusion and poor lighting conditions.